Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications. - David Ruhe; Giovanni Ciná; Michele Tonutti; Daan P. de Bruin; Paul W. G. Elbers (CoRR, 2019)

Self-Supervised Hybrid Inference in State-Space Models. - David Ruhe; Patrick Forré (CoRR, 2021)

Self-Supervised Inference in State-Space Models. - David Ruhe; Patrick Forré (ICLR, 2022)

Detecting dispersed radio transients in real time using convolutional neural networks. - David Ruhe; Mark Kuiack; Antonia Rowlinson; Ralph A. M. J. Wijers; Patrick Forré (Astron. Comput., 2022)

Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study. - David Ruhe; Kaze Wong; Miles D. Cranmer; Patrick Forré (CoRR, 2022)

Geometric Clifford Algebra Networks. - David Ruhe; Jayesh K. Gupta; Steven De Keninck; Max Welling; Johannes Brandstetter (ICML, 2023)

Clifford Group Equivariant Neural Networks. - David Ruhe; Johannes Brandstetter; Patrick Forré (NeurIPS, 2023)

On the Effectiveness of Hybrid Mutual Information Estimation. - Marco Federici; David Ruhe; Patrick Forré (CoRR, 2023)

Clifford Group Equivariant Simplicial Message Passing Networks. - Cong Liu; David Ruhe; Floor Eijkelboom; Patrick Forré (ICLR, 2024)

Rolling Diffusion Models. - David Ruhe; Jonathan Heek; Tim Salimans; Emiel Hoogeboom (ICML, 2024)

Clifford-Steerable Convolutional Neural Networks. - Maksim Zhdanov 001; David Ruhe; Maurice Weiler; Ana Lucic; Johannes Brandstetter; Patrick Forré (ICML, 2024)

Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural Networks. - Cong Liu; David Ruhe; Patrick Forré (CoRR, 2024)

Clifford Group Equivariant Diffusion Models for 3D Molecular Generation. - Cong Liu; Sharvaree Vadgama; David Ruhe; Erik J. Bekkers; Patrick Forré (CoRR, 2025)